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. 2011 Oct;38(10):5290-302.
doi: 10.1118/1.3633897.

Prostate implant reconstruction from C-arm images with motion-compensated tomosynthesis

Ehsan Dehghan  1 , Mehdi Moradi, Xu Wen, Danny French, Julio Lobo, W James Morris, Septimiu E Salcudean, Gabor Fichtinger
Affiliations

Prostate implant reconstruction from C-arm images with motion-compensated tomosynthesis

Ehsan Dehghan et al. Med Phys. 2011 Oct.

Abstract

Purpose: Accurate localization of prostate implants from several C-arm images is necessary for ultrasound-fluoroscopy fusion and intraoperative dosimetry. The authors propose a computational motion compensation method for tomosynthesis-based reconstruction that enables 3D localization of prostate implants from C-arm images despite C-arm oscillation and sagging.

Methods: Five C-arm images are captured by rotating the C-arm around its primary axis, while measuring its rotation angle using a protractor or the C-arm joint encoder. The C-arm images are processed to obtain binary seed-only images from which a volume of interest is reconstructed. The motion compensation algorithm, iteratively, compensates for 2D translational motion of the C-arm by maximizing the number of voxels that project on a seed projection in all of the images. This obviates the need for C-arm full pose tracking traditionally implemented using radio-opaque fiducials or external trackers. The proposed reconstruction method is tested in simulations, in a phantom study and on ten patient data sets.

Results: In a phantom implanted with 136 dummy seeds, the seed detection rate was 100% with a localization error of 0.86 ± 0.44 mm (Mean ± STD) compared to CT. For patient data sets, a detection rate of 99.5% was achieved in approximately 1 min per patient. The reconstruction results for patient data sets were compared against an available matching-based reconstruction method and showed relative localization difference of 0.5 ± 0.4 mm.

Conclusions: The motion compensation method can successfully compensate for large C-arm motion without using radio-opaque fiducial or external trackers. Considering the efficacy of the algorithm, its successful reconstruction rate and low computational burden, the algorithm is feasible for clinical use.

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Figures

Figure 1
Figure 1
A typical C-arm image of an implant showing some of the overlapping and hidden seeds. Localization of the seed projection centroids for hidden or overlapping seeds is difficult or sometimes impossible for seed segmentation methods.
Figure 2
Figure 2
Schematic of a C-arm rotating around its PA (rotation ①). Rotation ② shows rotation of the C-arm around its SA. The homogeneous world coordinate system Oxwywzw is centered at the center of rotation. The homogeneous source coordinate system Oxsyszs is centered at the source position corresponding to each image.
Figure 3
Figure 3
Left: a dilated seed-only image, right: labeled seed-only image.
Figure 4
Figure 4
Projection of two voxels on a seed-only image. In this projection, the voxel value of Voxel 1 is increased by one since Voxel 1 projects on a seed projection in this image. The voxel value of Voxel 2 is unchanged.
Figure 5
Figure 5
The total number of seed voxels in a VOI as a function of pose estimation errors. Errors are in the up–down direction (along zw) and perpendicular to the plane of rotation (along yw).
Figure 6
Figure 6
A band image used for motion compensation.
Figure 7
Figure 7
A false positive seed (white circle) and three true seeds (black circles). If any of the true seeds are removed, one cannot cover all the seed projections in the images.
Figure 8
Figure 8
Histogram of the seed cluster volumes for a real patient. Due to the wide range of cluster volumes, a predefined volume threshold cannot remove the FPs.
Figure 9
Figure 9
Simulation results, showing the average seed detection rate and localization error for variable pose errors. The average of seed detection rate for errors along yw and zw are shown in (a) and (b), respectively, for reconstructions with and without motion compensation. The mean and STD of localization error for errors along yw and zw are shown in (c) and (d), respectively, for reconstruction with motion compensation.
Figure 10
Figure 10
Reconstructed seed centroids projected on the C-arm image.
Figure 11
Figure 11
Reconstructed seed centroids. Seeds on the same strand are connected to each other.
See this image and copyright information in PMC

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